itk::GradientDescentOptimizer Class Reference
[Numerics, Optimizers]

Implement a gradient descent optimizer. More...

#include <itkGradientDescentOptimizer.h>

Inheritance diagram for itk::GradientDescentOptimizer:

[legend]Collaboration diagram for itk::GradientDescentOptimizer:

[legend]List of all members.

Public Types
typedef GradientDescentOptimizer	Self
typedef SingleValuedNonLinearOptimizer	Superclass
typedef SmartPointer< Self >	Pointer
typedef SmartPointer< const Self >	ConstPointer
enum	StopConditionType { MaximumNumberOfIterations, MetricError }
Public Member Functions
virtual const char *	GetClassName () const
virtual void	AdvanceOneStep (void)
void	StartOptimization (void)
void	ResumeOptimization (void)
void	StopOptimization (void)
virtual void	SetLearningRate (double _arg)
virtual double	GetLearningRate () const
virtual void	SetNumberOfIterations (unsigned long _arg)
virtual unsigned long	GetNumberOfIterations () const
virtual unsigned int	GetCurrentIteration () const
virtual double	GetValue () const
virtual StopConditionType	GetStopCondition () const
virtual bool	GetMaximize () const
virtual void	SetMaximize (bool _arg)
virtual void	MaximizeOn ()
virtual void	MaximizeOff ()
bool	GetMinimize () const
void	SetMinimize (bool v)
void	MinimizeOn ()
void	MinimizeOff ()
Static Public Member Functions
Pointer	New ()
Protected Member Functions
	GradientDescentOptimizer ()
virtual	~GradientDescentOptimizer ()
void	PrintSelf (std::ostream &os, Indent indent) const
Protected Attributes
DerivativeType	m_Gradient
bool	m_Maximize
double	m_LearningRate

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Detailed Description

Implement a gradient descent optimizer.

GradientDescentOptimizer implements a simple gradient descent optimizer. At each iteration the current position is updated according to

The learning rate is a fixed scalar defined via SetLearningRate(). The optimizer steps through a user defined number of iterations; no convergence checking is done.

Additionally, user can scale each component of the df / dp but setting a scaling vector using method SetScale().

See also:

RegularStepGradientDescentOptimizer

Definition at line 48 of file itkGradientDescentOptimizer.h.

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Member Typedef Documentation

typedef SmartPointer<const Self> itk::GradientDescentOptimizer::ConstPointer

Reimplemented from itk::SingleValuedNonLinearOptimizer. Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer. Definition at line 56 of file itkGradientDescentOptimizer.h.

typedef SmartPointer<Self> itk::GradientDescentOptimizer::Pointer

Reimplemented from itk::SingleValuedNonLinearOptimizer. Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer. Definition at line 55 of file itkGradientDescentOptimizer.h.

typedef GradientDescentOptimizer itk::GradientDescentOptimizer::Self

Standard class typedefs. Reimplemented from itk::SingleValuedNonLinearOptimizer. Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer. Definition at line 53 of file itkGradientDescentOptimizer.h.

typedef SingleValuedNonLinearOptimizer itk::GradientDescentOptimizer::Superclass

Reimplemented from itk::SingleValuedNonLinearOptimizer. Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer. Definition at line 54 of file itkGradientDescentOptimizer.h.

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Member Enumeration Documentation

enum itk::GradientDescentOptimizer::StopConditionType

Codes of stopping conditions Enumeration values: MaximumNumberOfIterations  MetricError  Definition at line 66 of file itkGradientDescentOptimizer.h.

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Constructor & Destructor Documentation

itk::GradientDescentOptimizer::GradientDescentOptimizer (   )  [protected]

virtual itk::GradientDescentOptimizer::~GradientDescentOptimizer (   )  [inline, protected, virtual]

Definition at line 123 of file itkGradientDescentOptimizer.h.

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Member Function Documentation

virtual void itk::GradientDescentOptimizer::AdvanceOneStep (  void   )  [virtual]

Advance one step following the gradient direction. Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer.

virtual const char* itk::GradientDescentOptimizer::GetClassName (   )  const [virtual]

Run-time type information (and related methods). Reimplemented from itk::SingleValuedNonLinearOptimizer. Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer.

virtual unsigned int itk::GradientDescentOptimizer::GetCurrentIteration (   )  const [virtual]

Get the current iteration number.

virtual double itk::GradientDescentOptimizer::GetLearningRate (   )  const [virtual]

Get the learning rate.

virtual bool itk::GradientDescentOptimizer::GetMaximize (   )  const [virtual]

Methods to configure the cost function.

bool itk::GradientDescentOptimizer::GetMinimize (   )  const [inline]

Methods to configure the cost function. Definition at line 75 of file itkGradientDescentOptimizer.h.

virtual unsigned long itk::GradientDescentOptimizer::GetNumberOfIterations (   )  const [virtual]

Get the number of iterations.

virtual StopConditionType itk::GradientDescentOptimizer::GetStopCondition (   )  const [virtual]

Get Stop condition.

virtual double itk::GradientDescentOptimizer::GetValue (   )  const [virtual]

Get the current value.

virtual void itk::GradientDescentOptimizer::MaximizeOff (   )  [virtual]

Methods to configure the cost function.

virtual void itk::GradientDescentOptimizer::MaximizeOn (   )  [virtual]

Methods to configure the cost function.

void itk::GradientDescentOptimizer::MinimizeOff (   )  [inline]

Methods to configure the cost function. Definition at line 81 of file itkGradientDescentOptimizer.h.

void itk::GradientDescentOptimizer::MinimizeOn (   )  [inline]

Methods to configure the cost function. Definition at line 79 of file itkGradientDescentOptimizer.h.

Pointer itk::GradientDescentOptimizer::New (   )  [static]

Method for creation through the object factory. Reimplemented from itk::SingleValuedNonLinearOptimizer. Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer.

void itk::GradientDescentOptimizer::PrintSelf (  std::ostream &  os, Indent  indent )  const [protected, virtual]

Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes. Reimplemented from itk::SingleValuedNonLinearOptimizer.

void itk::GradientDescentOptimizer::ResumeOptimization (  void   )

Resume previously stopped optimization with current parameters See also: StopOptimization.

virtual void itk::GradientDescentOptimizer::SetLearningRate (  double  _arg  )  [virtual]

Set the learning rate.

virtual void itk::GradientDescentOptimizer::SetMaximize (  bool  _arg  )  [virtual]

Methods to configure the cost function.

void itk::GradientDescentOptimizer::SetMinimize (  bool  v  )  [inline]

Methods to configure the cost function. Definition at line 77 of file itkGradientDescentOptimizer.h.

virtual void itk::GradientDescentOptimizer::SetNumberOfIterations (  unsigned long  _arg  )  [virtual]

Set the number of iterations.

void itk::GradientDescentOptimizer::StartOptimization (  void   )  [virtual]

Start optimization. Reimplemented from itk::Optimizer.

void itk::GradientDescentOptimizer::StopOptimization (  void   )

Stop optimization. See also: ResumeOptimization

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Member Data Documentation

DerivativeType itk::GradientDescentOptimizer::m_Gradient [protected]

Definition at line 128 of file itkGradientDescentOptimizer.h.

double itk::GradientDescentOptimizer::m_LearningRate [protected]

Definition at line 130 of file itkGradientDescentOptimizer.h.

bool itk::GradientDescentOptimizer::m_Maximize [protected]

Definition at line 129 of file itkGradientDescentOptimizer.h.

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The documentation for this class was generated from the following file:

• itkGradientDescentOptimizer.h

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